Copulation rate declines with mating group size in dusky dolphins (<i>Lagenorhynchus</i> <i>obscurus</i>)
Bibliographic record
Abstract
Males in polygamous species often engage in intrasexual competition for mates. If females actively evade mating attempts, it may benefit males to cooperate to restrict female movement, as has been found in some mammals. We tested if male dusky dolphins (Lagenorhynchus obscurus (Gray, 1828)) cooperate or compete during group mating chases. If they cooperate, then the per-male probability of copulating should increase with group size; if they compete, then the probability should decrease. We followed mating groups by boat during the breeding season (October 2013 – January 2014) off Kaikoura, New Zealand. The copulation rate per male decreased with increasing group size and with the number of noncopulating males in proximity to a copulating female. Male dusky dolphins have multiple mates and appear to use sperm and exploitative scramble competition. Males may remain in mating groups despite competition because there are alliances within the groups, they are unable to exclude rivals from joining a group, the time and energy costs of searching for unescorted females exceed the costs of reduced mating opportunities in a group, they receive other direct or indirect benefits that offset the costs of reduced mating opportunities, or they are in the group largely for social learning rather than procreation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".